Field of the Invention
The present invention relates to an adaptive device and an adaptive method for classifying objects, particularly to an adaptive device and an adaptive method for classifying objects with parallel architecture.
Description of the Related Art
In recent years, driving safety is more concerned. With the decreased cost of image equipments and development of image recognition, an image recognition system has more widely applied to driving safety. Besides, an image recognition technology is an important method to reduce the cost of a safe system. Statistically, as long as a driver is warned 0.5 second before collisions, rear-end collision accidents with a percentage of at least 60%, head-on collision accidents with a percentage of 30% and road-related accidents with a percentage of 50% are avoided. If the warning time is 1 second, the accidents with 90% are avoided. It is difficult for the image recognition system to calculate a large of data amount. How to deal with a large of data amount in a vehicle safe system requiring strictly performing real time operations is more concerned.
A pedestrian detection system used in an automatic emergency braking (AEB) system is realized with very expensive equipment, such as an infrared ray detection device or a laser radar detection device. Road scenes are complicated. For example, a scene has pedestrians, vehicles, cats and dogs. As a result, the stronger characteristic parameters are needed to separate the pedestrians from the other backgrounds. Additionally, during a detection process of the pedestrian detection system, the precision of detection results is decreased due to the disturbances of various environment factors of sets. For example, the environment with uneven illumination makes a part of the pedestrians too bright or too dark. Alternatively, it is often not accurate to determine whether a pedestrian exists in a scene under a condition of a body of the pedestrian partially shielded. There is another pedestrian detection method which uses a background-retrieving technology to obtain foregrounds for further processing. However, the foregrounds are more broken whereby the rear end is difficult to recognize them. Besides, the technology costs a lot of time to retrieve images, which imposes a burden on the system. As a result, how to improve the efficiency of detecting obstructions and to achieve real time detection requirements is a problem to be solved.
To overcome the abovementioned problems, the present invention provides an adaptive device and an adaptive method for classifying objects with parallel architecture, so as to solve the afore-mentioned problems of the prior art.